distilbert-base-uncased-lora-text-classification

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9682
• Accuracy: {'accuracy': 0.89}

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.4717	{'accuracy': 0.863}
0.4304	2.0	500	0.4826	{'accuracy': 0.865}
0.4304	3.0	750	0.6937	{'accuracy': 0.873}
0.1783	4.0	1000	0.6554	{'accuracy': 0.896}
0.1783	5.0	1250	0.8139	{'accuracy': 0.891}
0.0536	6.0	1500	0.7892	{'accuracy': 0.896}
0.0536	7.0	1750	0.8994	{'accuracy': 0.898}
0.0185	8.0	2000	0.9587	{'accuracy': 0.892}
0.0185	9.0	2250	0.9562	{'accuracy': 0.893}
0.0027	10.0	2500	0.9682	{'accuracy': 0.89}

Framework versions

• PEFT 0.9.0
• Transformers 4.38.2
• Pytorch 2.2.1+cpu
• Datasets 2.18.0
• Tokenizers 0.15.2